Email this article 
Detection of Tears on Document Page Using Analysis of Infrared Image
- Authors: Padas O.A.1, Kunina I.A.2
-
Affiliations:
- Smart Engines Service LLC
- Institute for Information Transmission Problems of RAS (Kharkevich Institute)
- Issue: No 2 (2024)
- Pages: 65-73
- Section: Intelligent systems and technologies
- URL: https://journals.rcsi.science/2071-8632/article/view/288008
- DOI: https://doi.org/10.14357/20718632240206
- EDN: https://elibrary.ru/UVEKWC
- ID: 288008
Cite item
Open Access
Access granted
Subscription Access
Abstract
This paper examines the problem of detecting tears on a protected document page. We present an approach based on analyzing the document image in the infrared range. It is assumed that in this case it is possible to separate the damage from the protective elements applied by IR-transparent inks. So the problem of tears detection might be reduced to a search for thin lines of a certain length adjacent to the border of the document page. Thus, we developed a tear search algorithm based on the search for "ridge" type lines followed by checking whether the line satisfies the specified properties. We created and pub- lished a VIUR dataset with Russian banknotes in order to test the algorithm. The recall of the proposed algorithm is 0.87, the precision is 0.94.
Keywords
About the authors
Olga A. Padas
Smart Engines Service LLC
Author for correspondence.
Email: o.padas@smartengines.com
Research interests are image pro- cessing, computer vision
Russian Federation, MoscowIrina A. Kunina
Institute for Information Transmission Problems of RAS (Kharkevich Institute)
Email: i.kunina@smartengines.com
Ph.D in Technical Science
Russian Federation, MoscowReferences
- Awal, A. M., Ghanmi, N., Sicre, R., Furon, T.. Complex document classification and localization application on identity document images. 14th IAPR International Conference on Document Analysis and Recognition (ICDAR), 2017; 1: 426-431.
- Attivissimo, F., Giaquinto, N., Scarpetta, M., & Spadavecchia, M. An automatic reader of identity documents. IEEE International Conference on Systems, Man and Cybernetics (SMC). 2019; p. 3525-3530.
- Arlazarov, V. L., Arlazarov, V. V., Bulatov, K. B., Chernov, T. S., Nikolaev, D. P., Polevoy, D. V., ... , Usilin, S. A.. Mobile ID Document Recognition–Coarse-to-Fine Ap- proach. Pattern Recognition and Image Analysis. 2022; 32(1): 89-108.
- Chernyshova, Y. S., Aliev, M. A., Gushchanskaia, E. S., Sheshkus, A. V. Optical font recognition in smartphonecaptured images and its applicability for ID forgery detection. Eleventh International Conference on Machine Vision (ICMV 2018). 2018; 11041: 402-409.
- Kada, O., Kurtz, C., van Kieu, C., Vincent, N.. Hologram Detection for Identity Document Authentication. International Conference on Pattern Recognition and Artificial In- telligence. Cham: Springer International Publishing. 2022;
- p. 346-357.
- Koliaskina, L. I., Emelianova, E. V., Tropin, D. V., Popov,V. V., Bulatov, K. B., Nikolaev, D. P., Arlazarov, V. V. MIDV-Holo: A Dataset for ID Document Hologram Detection in a Video Stream. International Conference on Document Analysis and Recognition. Cham: Springer Nature Switzerland. 2023; 486-503.
- Polevoy D. V., Panfilova E. I., Nikolaev D. P.. White balance correction for detection of holograms in color images of black and white photographs. ITiVS. 2021; 3: 82-95. doi: 10.14357/20718632210308.
- Valov M. A., Matalov D. P., Usilin S. A.. The use of centrally symmetric Haar features for stamp localization on the passport of a citizen of the Russian Federation. Trudy ISA RAN (Proceedings of ISA RAS). 2023; 73(3): 31-3. doi: 10.14357/20790279230304. (In Russ)
- Schityvatel' Dokumentov PS4-02 PSHNK.468469.009. Available from: http://ex-pertprospb.ru/2019/05/31/schityvatel-dokumentov-ps4-02- pshnk-468469-009/ [Accessed 13 October 2023]. (In Russ)
- Passport Scanner With RFID OCR4000. Available from: http://www.tenkoto.com/en/Products/pos/2019/0827/Read er/Passport.html [Accessed 13 October 2023].
- Kunina, I. A., Aliev, M. A., Arlazarov, N. V., & Polevoy,D. V.. A method of fluorescent fibers detection on identity documents under ultraviolet light. Twelfth International Conference on Machine Vision (ICMV 2019). 2020; 11433:89-96.
- Kaur, A., Raj, A., Jayanthi, N., Indu, S.. Inpainting of irregular holes in a manuscript using unet and partial convolution. 2020 Second International Conference on Inventive Research in Computing Applications (ICIRCA). 2020; p 778-784.
- Hedjam, R., Cheriet, M.. Historical document image resto- ration using multispectral imaging system. Pattern Recognition. 2013; 46(8): 2297-2312.
- de Sá Soares, A., das Neves Junior, R. B., Bezerra, B. L. D.. BID Dataset: a challenge dataset for document processing tasks. Anais Estendidos do XXXIII Conference on Graphics, Patterns and Images. SBC, 2020; p. 143-146.
- Bulatovich, B. K., Vladimirovna, E. E., Vyacheslavovich,
- T. D., Sergeevna, S. N., Sergeevna, C. Y., Zuheng, M., ..., Muzzamil, L. M. MIDV-2020: a comprehensive bench- mark dataset for identity document analysis. Computer Optics. 2022; 46(2): 252-270.
- Polevoy D. V., Sigareva I. V., Ershova D. M., Arlazarov
- V. V., Nikolaev D. P., Zuheng M., Muhammad M. L., Burie J.. Document Liveness Challenge dataset (DLC- 2021). Journal of Imaging. 2022; 8(7). 181. doi: 10.3390/jimaging8070181.
- Tropin D. V., Shemyakina Y. A., Konovalenko I. A., Faradjev I. A.. Localization of planar objects on the images with complex structure of projective distortion. Informatsionnye protsessy. 2019; 19(2): 208-229. (In Russ)
- Skaner Dokumentov SD-03 PSHNK.468469.016. Availa- ble from: http://expertprospb.ru/2021/09/07/skaner- dokumentov-sd-03-pshnk-468469-016/. [Accessed: 13 October 2023]. (In Russ)
Supplementary files
